Source 1review2024Neurochemistry International
Toolkit/qRT-PCR
qRT-PCR
Also known as: qRT-PCR, qRTPCR, quantitative analysis of gene expression by qRTPCR
Taxonomy: Technique Branch / Method. Workflows sit above the mechanism and technique branches rather than replacing them.
Summary
qRT-PCR is a quantitative reverse-transcription PCR assay used to measure transcript abundance, here applied to GFP mRNA during light-controlled gene expression in Synechococcus sp. PCC 7002. In the cited study, it quantified transcriptional activation and deactivation kinetics of optogenetic systems under green/red and light/dark illumination cycles.
Usefulness & Problems
Why this is useful
This assay is useful for resolving transcriptional responses of optogenetic circuits at the mRNA level under defined illumination programs. In the supplied evidence, it enabled kinetic measurement of GFP transcript changes and comparison of system performance across multiple green/red and light/dark cycles.
Source:
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Source:
In this protocol, an optogenetic expression system is used to achieve light-inducible gene expression in zebrafish embryos.
Problem solved
qRT-PCR addresses the need to quantify how rapidly and reversibly light-regulated gene expression systems change transcriptional output. In this context, it provided a way to measure activation and deactivation kinetics of GFP transcription in response to optogenetic stimulation.
Source:
In this protocol, an optogenetic expression system is used to achieve light-inducible gene expression in zebrafish embryos.
Problem links
Need precise spatiotemporal control with light input
DerivedqRT-PCR is a quantitative reverse-transcription PCR assay used here to measure GFP transcript abundance during light-controlled gene expression. In Synechococcus sp. PCC 7002, it was used to quantify transcriptional activation and deactivation kinetics of optogenetic systems under green/red and light/dark illumination cycles.
Need tighter control over gene expression timing or amplitude
DerivedqRT-PCR is a quantitative reverse-transcription PCR assay used here to measure GFP transcript abundance during light-controlled gene expression. In Synechococcus sp. PCC 7002, it was used to quantify transcriptional activation and deactivation kinetics of optogenetic systems under green/red and light/dark illumination cycles.
Taxonomy & Function
Primary hierarchy
Technique Branch
Method: A concrete measurement method used to characterize an engineered system.
Mechanisms
fluorescence-based nucleic acid quantificationfluorescence-based nucleic acid quantificationpolymerase chain reaction amplificationpolymerase chain reaction amplificationreverse transcriptionreverse transcriptionTarget processes
diagnostictranscriptionInput: Light
Implementation Constraints
cofactor dependency: cofactor requirement unknowndomain: Alzheimer's disease researchencoding mode: genetically encodedimplementation constraint: context specific validationimplementation constraint: spectral hardware requirementoperating role: sensorreadout level: transcripttool role: gene expression assay
The evidence indicates use of qRT-PCR to monitor GFP transcript abundance in Synechococcus sp. PCC 7002 during green/red and light/dark illumination experiments. Beyond its basis in reverse transcription, PCR amplification, and fluorescence-based nucleic acid quantification, the supplied sources do not specify reagents, instrument settings, or construct design requirements.
The supplied evidence only supports use as a transcript quantification assay and does not provide details on assay sensitivity, normalization strategy, primer design, or absolute performance metrics. Validation in the provided claims is limited to GFP transcript monitoring in one cyanobacterial optogenetic context.
Validation
Cell-freeBacteriaMammalianMouseHumanTherapeuticIndep. Replication
Observations
successBacteriaapplication demoSynechococcus sp. PCC 7002
qRT-PCR
Inferred from claim claim3 during normalization. Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance. Derived from claim claim3. Quoted text: Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Source:
successBacteriaapplication demoSynechococcus sp. PCC 7002
qRT-PCR
Inferred from claim claim3 during normalization. Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance. Derived from claim claim3. Quoted text: Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Source:
successBacteriaapplication demoSynechococcus sp. PCC 7002
qRT-PCR
Inferred from claim claim3 during normalization. Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance. Derived from claim claim3. Quoted text: Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Source:
successBacteriaapplication demoSynechococcus sp. PCC 7002
qRT-PCR
Inferred from claim claim3 during normalization. Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance. Derived from claim claim3. Quoted text: Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Source:
successBacteriaapplication demoSynechococcus sp. PCC 7002
qRT-PCR
Inferred from claim claim3 during normalization. Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance. Derived from claim claim3. Quoted text: Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Source:
successBacteriaapplication demoSynechococcus sp. PCC 7002
qRT-PCR
Inferred from claim claim3 during normalization. Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance. Derived from claim claim3. Quoted text: Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Source:
successBacteriaapplication demoSynechococcus sp. PCC 7002
qRT-PCR
Inferred from claim claim3 during normalization. Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance. Derived from claim claim3. Quoted text: Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Source:
successBacteriaapplication demoSynechococcus sp. PCC 7002
qRT-PCR
Inferred from claim claim3 during normalization. Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance. Derived from claim claim3. Quoted text: Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Source:
Supporting Sources
Source 2primary paper2025MED
Source 3primary paper2021Journal of Visualized Experiments
Source 4primary paper2024MED
Ranked Claims
AkWRKY38 and AkWRKY53 exhibited high expression levels in Amorphophallus konjac under hormone treatments, Pcc infection, and abiotic stresses including low temperature, drought, and salt stress.
Fourteen AkWRKY genes showed significantly differential expression under ABA, JA, SA, Pectobacterium carotovorum subsp. carotovorum infection, low temperature, drought, and salt stress.
AkWRKY genes profiled by qRT-PCR under stress 14
Targeted genetic modifications to the pCpcG2 output promoter increased CcaS/CcaR system activity under green light.
Finally, we increased CcaS/CcaR system activity under green light through targeted genetic modifications to the <i>pCpcG2</i> output promoter.
Targeted genetic modifications to the pCpcG2 output promoter increased CcaS/CcaR system activity under green light.
Finally, we increased CcaS/CcaR system activity under green light through targeted genetic modifications to the <i>pCpcG2</i> output promoter.
Targeted genetic modifications to the pCpcG2 output promoter increased CcaS/CcaR system activity under green light.
Finally, we increased CcaS/CcaR system activity under green light through targeted genetic modifications to the <i>pCpcG2</i> output promoter.
Targeted genetic modifications to the pCpcG2 output promoter increased CcaS/CcaR system activity under green light.
Finally, we increased CcaS/CcaR system activity under green light through targeted genetic modifications to the <i>pCpcG2</i> output promoter.
Targeted genetic modifications to the pCpcG2 output promoter increased CcaS/CcaR system activity under green light.
Finally, we increased CcaS/CcaR system activity under green light through targeted genetic modifications to the <i>pCpcG2</i> output promoter.
Targeted genetic modifications to the pCpcG2 output promoter increased CcaS/CcaR system activity under green light.
Finally, we increased CcaS/CcaR system activity under green light through targeted genetic modifications to the <i>pCpcG2</i> output promoter.
Targeted genetic modifications to the pCpcG2 output promoter increased CcaS/CcaR system activity under green light.
Finally, we increased CcaS/CcaR system activity under green light through targeted genetic modifications to the <i>pCpcG2</i> output promoter.
Targeted genetic modifications to the pCpcG2 output promoter increased CcaS/CcaR system activity under green light.
Finally, we increased CcaS/CcaR system activity under green light through targeted genetic modifications to the <i>pCpcG2</i> output promoter.
Targeted genetic modifications to the pCpcG2 output promoter increased CcaS/CcaR system activity under green light.
Finally, we increased CcaS/CcaR system activity under green light through targeted genetic modifications to the <i>pCpcG2</i> output promoter.
Targeted genetic modifications to the pCpcG2 output promoter increased CcaS/CcaR system activity under green light.
Finally, we increased CcaS/CcaR system activity under green light through targeted genetic modifications to the <i>pCpcG2</i> output promoter.
Targeted genetic modifications to the pCpcG2 output promoter increased CcaS/CcaR system activity under green light.
Finally, we increased CcaS/CcaR system activity under green light through targeted genetic modifications to the <i>pCpcG2</i> output promoter.
Targeted genetic modifications to the pCpcG2 output promoter increased CcaS/CcaR system activity under green light.
Finally, we increased CcaS/CcaR system activity under green light through targeted genetic modifications to the <i>pCpcG2</i> output promoter.
Targeted genetic modifications to the pCpcG2 output promoter increased CcaS/CcaR system activity under green light.
Finally, we increased CcaS/CcaR system activity under green light through targeted genetic modifications to the <i>pCpcG2</i> output promoter.
Targeted genetic modifications to the pCpcG2 output promoter increased CcaS/CcaR system activity under green light.
Finally, we increased CcaS/CcaR system activity under green light through targeted genetic modifications to the <i>pCpcG2</i> output promoter.
Targeted genetic modifications to the pCpcG2 output promoter increased CcaS/CcaR system activity under green light.
Finally, we increased CcaS/CcaR system activity under green light through targeted genetic modifications to the <i>pCpcG2</i> output promoter.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
In <i>Synechococcus</i> sp. PCC 7002, the CcaS/CcaR system responded well to light wavelengths and intensities and produced a 6-fold increase in protein fluorescence output after 30 min of green light.
the CcaS/CcaR system originating from the cyanobacterium <i>Synechocystis</i> sp. PCC 6803 responded well to light wavelengths and intensities, with a 6-fold increased protein fluorescence output observed after 30 min of green light.
protein fluorescence output increase 6 fold
In <i>Synechococcus</i> sp. PCC 7002, the CcaS/CcaR system responded well to light wavelengths and intensities and produced a 6-fold increase in protein fluorescence output after 30 min of green light.
the CcaS/CcaR system originating from the cyanobacterium <i>Synechocystis</i> sp. PCC 6803 responded well to light wavelengths and intensities, with a 6-fold increased protein fluorescence output observed after 30 min of green light.
protein fluorescence output increase 6 fold
In <i>Synechococcus</i> sp. PCC 7002, the CcaS/CcaR system responded well to light wavelengths and intensities and produced a 6-fold increase in protein fluorescence output after 30 min of green light.
the CcaS/CcaR system originating from the cyanobacterium <i>Synechocystis</i> sp. PCC 6803 responded well to light wavelengths and intensities, with a 6-fold increased protein fluorescence output observed after 30 min of green light.
protein fluorescence output increase 6 fold
In <i>Synechococcus</i> sp. PCC 7002, the CcaS/CcaR system responded well to light wavelengths and intensities and produced a 6-fold increase in protein fluorescence output after 30 min of green light.
the CcaS/CcaR system originating from the cyanobacterium <i>Synechocystis</i> sp. PCC 6803 responded well to light wavelengths and intensities, with a 6-fold increased protein fluorescence output observed after 30 min of green light.
protein fluorescence output increase 6 fold
In <i>Synechococcus</i> sp. PCC 7002, the CcaS/CcaR system responded well to light wavelengths and intensities and produced a 6-fold increase in protein fluorescence output after 30 min of green light.
the CcaS/CcaR system originating from the cyanobacterium <i>Synechocystis</i> sp. PCC 6803 responded well to light wavelengths and intensities, with a 6-fold increased protein fluorescence output observed after 30 min of green light.
protein fluorescence output increase 6 fold
In <i>Synechococcus</i> sp. PCC 7002, the CcaS/CcaR system responded well to light wavelengths and intensities and produced a 6-fold increase in protein fluorescence output after 30 min of green light.
the CcaS/CcaR system originating from the cyanobacterium <i>Synechocystis</i> sp. PCC 6803 responded well to light wavelengths and intensities, with a 6-fold increased protein fluorescence output observed after 30 min of green light.
protein fluorescence output increase 6 fold
In <i>Synechococcus</i> sp. PCC 7002, the CcaS/CcaR system responded well to light wavelengths and intensities and produced a 6-fold increase in protein fluorescence output after 30 min of green light.
the CcaS/CcaR system originating from the cyanobacterium <i>Synechocystis</i> sp. PCC 6803 responded well to light wavelengths and intensities, with a 6-fold increased protein fluorescence output observed after 30 min of green light.
protein fluorescence output increase 6 fold
In <i>Synechococcus</i> sp. PCC 7002, the CcaS/CcaR system responded well to light wavelengths and intensities and produced a 6-fold increase in protein fluorescence output after 30 min of green light.
the CcaS/CcaR system originating from the cyanobacterium <i>Synechocystis</i> sp. PCC 6803 responded well to light wavelengths and intensities, with a 6-fold increased protein fluorescence output observed after 30 min of green light.
protein fluorescence output increase 6 fold
In <i>Synechococcus</i> sp. PCC 7002, the CcaS/CcaR system responded well to light wavelengths and intensities and produced a 6-fold increase in protein fluorescence output after 30 min of green light.
the CcaS/CcaR system originating from the cyanobacterium <i>Synechocystis</i> sp. PCC 6803 responded well to light wavelengths and intensities, with a 6-fold increased protein fluorescence output observed after 30 min of green light.
protein fluorescence output increase 6 fold
In <i>Synechococcus</i> sp. PCC 7002, the CcaS/CcaR system responded well to light wavelengths and intensities and produced a 6-fold increase in protein fluorescence output after 30 min of green light.
the CcaS/CcaR system originating from the cyanobacterium <i>Synechocystis</i> sp. PCC 6803 responded well to light wavelengths and intensities, with a 6-fold increased protein fluorescence output observed after 30 min of green light.
protein fluorescence output increase 6 fold
In <i>Synechococcus</i> sp. PCC 7002, the CcaS/CcaR system responded well to light wavelengths and intensities and produced a 6-fold increase in protein fluorescence output after 30 min of green light.
the CcaS/CcaR system originating from the cyanobacterium <i>Synechocystis</i> sp. PCC 6803 responded well to light wavelengths and intensities, with a 6-fold increased protein fluorescence output observed after 30 min of green light.
protein fluorescence output increase 6 fold
In <i>Synechococcus</i> sp. PCC 7002, the CcaS/CcaR system responded well to light wavelengths and intensities and produced a 6-fold increase in protein fluorescence output after 30 min of green light.
the CcaS/CcaR system originating from the cyanobacterium <i>Synechocystis</i> sp. PCC 6803 responded well to light wavelengths and intensities, with a 6-fold increased protein fluorescence output observed after 30 min of green light.
protein fluorescence output increase 6 fold
In <i>Synechococcus</i> sp. PCC 7002, the CcaS/CcaR system responded well to light wavelengths and intensities and produced a 6-fold increase in protein fluorescence output after 30 min of green light.
the CcaS/CcaR system originating from the cyanobacterium <i>Synechocystis</i> sp. PCC 6803 responded well to light wavelengths and intensities, with a 6-fold increased protein fluorescence output observed after 30 min of green light.
protein fluorescence output increase 6 fold
In <i>Synechococcus</i> sp. PCC 7002, the CcaS/CcaR system responded well to light wavelengths and intensities and produced a 6-fold increase in protein fluorescence output after 30 min of green light.
the CcaS/CcaR system originating from the cyanobacterium <i>Synechocystis</i> sp. PCC 6803 responded well to light wavelengths and intensities, with a 6-fold increased protein fluorescence output observed after 30 min of green light.
protein fluorescence output increase 6 fold
In <i>Synechococcus</i> sp. PCC 7002, the CcaS/CcaR system responded well to light wavelengths and intensities and produced a 6-fold increase in protein fluorescence output after 30 min of green light.
the CcaS/CcaR system originating from the cyanobacterium <i>Synechocystis</i> sp. PCC 6803 responded well to light wavelengths and intensities, with a 6-fold increased protein fluorescence output observed after 30 min of green light.
protein fluorescence output increase 6 fold
In <i>Synechococcus</i> sp. PCC 7002, the YF1/FixJ system showed poor performance with a maximum dynamic range of 1.5-fold.
The YF1/FixJ system of non-cyanobacterial origin showed poor performance with a maximum dynamic range of 1.5-fold despite several steps to improve this.
maximum dynamic range 1.5 fold
In <i>Synechococcus</i> sp. PCC 7002, the YF1/FixJ system showed poor performance with a maximum dynamic range of 1.5-fold.
The YF1/FixJ system of non-cyanobacterial origin showed poor performance with a maximum dynamic range of 1.5-fold despite several steps to improve this.
maximum dynamic range 1.5 fold
In <i>Synechococcus</i> sp. PCC 7002, the YF1/FixJ system showed poor performance with a maximum dynamic range of 1.5-fold.
The YF1/FixJ system of non-cyanobacterial origin showed poor performance with a maximum dynamic range of 1.5-fold despite several steps to improve this.
maximum dynamic range 1.5 fold
In <i>Synechococcus</i> sp. PCC 7002, the YF1/FixJ system showed poor performance with a maximum dynamic range of 1.5-fold.
The YF1/FixJ system of non-cyanobacterial origin showed poor performance with a maximum dynamic range of 1.5-fold despite several steps to improve this.
maximum dynamic range 1.5 fold
In <i>Synechococcus</i> sp. PCC 7002, the YF1/FixJ system showed poor performance with a maximum dynamic range of 1.5-fold.
The YF1/FixJ system of non-cyanobacterial origin showed poor performance with a maximum dynamic range of 1.5-fold despite several steps to improve this.
maximum dynamic range 1.5 fold
In <i>Synechococcus</i> sp. PCC 7002, the YF1/FixJ system showed poor performance with a maximum dynamic range of 1.5-fold.
The YF1/FixJ system of non-cyanobacterial origin showed poor performance with a maximum dynamic range of 1.5-fold despite several steps to improve this.
maximum dynamic range 1.5 fold
In <i>Synechococcus</i> sp. PCC 7002, the YF1/FixJ system showed poor performance with a maximum dynamic range of 1.5-fold.
The YF1/FixJ system of non-cyanobacterial origin showed poor performance with a maximum dynamic range of 1.5-fold despite several steps to improve this.
maximum dynamic range 1.5 fold
In <i>Synechococcus</i> sp. PCC 7002, the YF1/FixJ system showed poor performance with a maximum dynamic range of 1.5-fold.
The YF1/FixJ system of non-cyanobacterial origin showed poor performance with a maximum dynamic range of 1.5-fold despite several steps to improve this.
maximum dynamic range 1.5 fold
In <i>Synechococcus</i> sp. PCC 7002, the YF1/FixJ system showed poor performance with a maximum dynamic range of 1.5-fold.
The YF1/FixJ system of non-cyanobacterial origin showed poor performance with a maximum dynamic range of 1.5-fold despite several steps to improve this.
maximum dynamic range 1.5 fold
In <i>Synechococcus</i> sp. PCC 7002, the YF1/FixJ system showed poor performance with a maximum dynamic range of 1.5-fold.
The YF1/FixJ system of non-cyanobacterial origin showed poor performance with a maximum dynamic range of 1.5-fold despite several steps to improve this.
maximum dynamic range 1.5 fold
In <i>Synechococcus</i> sp. PCC 7002, the YF1/FixJ system showed poor performance with a maximum dynamic range of 1.5-fold.
The YF1/FixJ system of non-cyanobacterial origin showed poor performance with a maximum dynamic range of 1.5-fold despite several steps to improve this.
maximum dynamic range 1.5 fold
In <i>Synechococcus</i> sp. PCC 7002, the YF1/FixJ system showed poor performance with a maximum dynamic range of 1.5-fold.
The YF1/FixJ system of non-cyanobacterial origin showed poor performance with a maximum dynamic range of 1.5-fold despite several steps to improve this.
maximum dynamic range 1.5 fold
In <i>Synechococcus</i> sp. PCC 7002, the YF1/FixJ system showed poor performance with a maximum dynamic range of 1.5-fold.
The YF1/FixJ system of non-cyanobacterial origin showed poor performance with a maximum dynamic range of 1.5-fold despite several steps to improve this.
maximum dynamic range 1.5 fold
In <i>Synechococcus</i> sp. PCC 7002, the YF1/FixJ system showed poor performance with a maximum dynamic range of 1.5-fold.
The YF1/FixJ system of non-cyanobacterial origin showed poor performance with a maximum dynamic range of 1.5-fold despite several steps to improve this.
maximum dynamic range 1.5 fold
In <i>Synechococcus</i> sp. PCC 7002, the YF1/FixJ system showed poor performance with a maximum dynamic range of 1.5-fold.
The YF1/FixJ system of non-cyanobacterial origin showed poor performance with a maximum dynamic range of 1.5-fold despite several steps to improve this.
maximum dynamic range 1.5 fold
The review presents qRT-PCR and iPSC-based mitochondrial-function evaluation as advances in diagnostic and research tools for Alzheimer's disease.
This study underlines the complexity of transferring optogenetic tools across species.
This study provides a detailed characterisation of the behaviour of the CcaS/CcaR system in <i>Synechococcus</i> sp. PCC 7002, as well as underlining the complexity of transferring optogenetic tools across species.
This study underlines the complexity of transferring optogenetic tools across species.
This study provides a detailed characterisation of the behaviour of the CcaS/CcaR system in <i>Synechococcus</i> sp. PCC 7002, as well as underlining the complexity of transferring optogenetic tools across species.
This study underlines the complexity of transferring optogenetic tools across species.
This study provides a detailed characterisation of the behaviour of the CcaS/CcaR system in <i>Synechococcus</i> sp. PCC 7002, as well as underlining the complexity of transferring optogenetic tools across species.
This study underlines the complexity of transferring optogenetic tools across species.
This study provides a detailed characterisation of the behaviour of the CcaS/CcaR system in <i>Synechococcus</i> sp. PCC 7002, as well as underlining the complexity of transferring optogenetic tools across species.
This study underlines the complexity of transferring optogenetic tools across species.
This study provides a detailed characterisation of the behaviour of the CcaS/CcaR system in <i>Synechococcus</i> sp. PCC 7002, as well as underlining the complexity of transferring optogenetic tools across species.
This study underlines the complexity of transferring optogenetic tools across species.
This study provides a detailed characterisation of the behaviour of the CcaS/CcaR system in <i>Synechococcus</i> sp. PCC 7002, as well as underlining the complexity of transferring optogenetic tools across species.
This study underlines the complexity of transferring optogenetic tools across species.
This study provides a detailed characterisation of the behaviour of the CcaS/CcaR system in <i>Synechococcus</i> sp. PCC 7002, as well as underlining the complexity of transferring optogenetic tools across species.
This study underlines the complexity of transferring optogenetic tools across species.
This study provides a detailed characterisation of the behaviour of the CcaS/CcaR system in <i>Synechococcus</i> sp. PCC 7002, as well as underlining the complexity of transferring optogenetic tools across species.
This study underlines the complexity of transferring optogenetic tools across species.
This study provides a detailed characterisation of the behaviour of the CcaS/CcaR system in <i>Synechococcus</i> sp. PCC 7002, as well as underlining the complexity of transferring optogenetic tools across species.
This study underlines the complexity of transferring optogenetic tools across species.
This study provides a detailed characterisation of the behaviour of the CcaS/CcaR system in <i>Synechococcus</i> sp. PCC 7002, as well as underlining the complexity of transferring optogenetic tools across species.
This study underlines the complexity of transferring optogenetic tools across species.
This study provides a detailed characterisation of the behaviour of the CcaS/CcaR system in <i>Synechococcus</i> sp. PCC 7002, as well as underlining the complexity of transferring optogenetic tools across species.
This study underlines the complexity of transferring optogenetic tools across species.
This study provides a detailed characterisation of the behaviour of the CcaS/CcaR system in <i>Synechococcus</i> sp. PCC 7002, as well as underlining the complexity of transferring optogenetic tools across species.
This study underlines the complexity of transferring optogenetic tools across species.
This study provides a detailed characterisation of the behaviour of the CcaS/CcaR system in <i>Synechococcus</i> sp. PCC 7002, as well as underlining the complexity of transferring optogenetic tools across species.
This study underlines the complexity of transferring optogenetic tools across species.
This study provides a detailed characterisation of the behaviour of the CcaS/CcaR system in <i>Synechococcus</i> sp. PCC 7002, as well as underlining the complexity of transferring optogenetic tools across species.
This study underlines the complexity of transferring optogenetic tools across species.
This study provides a detailed characterisation of the behaviour of the CcaS/CcaR system in <i>Synechococcus</i> sp. PCC 7002, as well as underlining the complexity of transferring optogenetic tools across species.
The TAEL/C120 system is used to achieve light-inducible gene expression in zebrafish embryos.
In this protocol, an optogenetic expression system is used to achieve light-inducible gene expression in zebrafish embryos.
The TAEL/C120 system is used to achieve light-inducible gene expression in zebrafish embryos.
In this protocol, an optogenetic expression system is used to achieve light-inducible gene expression in zebrafish embryos.
The TAEL/C120 system is used to achieve light-inducible gene expression in zebrafish embryos.
In this protocol, an optogenetic expression system is used to achieve light-inducible gene expression in zebrafish embryos.
The TAEL/C120 system is used to achieve light-inducible gene expression in zebrafish embryos.
In this protocol, an optogenetic expression system is used to achieve light-inducible gene expression in zebrafish embryos.
The TAEL/C120 system is used to achieve light-inducible gene expression in zebrafish embryos.
In this protocol, an optogenetic expression system is used to achieve light-inducible gene expression in zebrafish embryos.
Blue light causes TAEL to dimerize, bind C120, and activate transcription.
When illuminated with blue light, TAEL dimerizes, binds to its cognate regulatory element called C120, and activates transcription.
Blue light causes TAEL to dimerize, bind C120, and activate transcription.
When illuminated with blue light, TAEL dimerizes, binds to its cognate regulatory element called C120, and activates transcription.
Blue light causes TAEL to dimerize, bind C120, and activate transcription.
When illuminated with blue light, TAEL dimerizes, binds to its cognate regulatory element called C120, and activates transcription.
Blue light causes TAEL to dimerize, bind C120, and activate transcription.
When illuminated with blue light, TAEL dimerizes, binds to its cognate regulatory element called C120, and activates transcription.
Blue light causes TAEL to dimerize, bind C120, and activate transcription.
When illuminated with blue light, TAEL dimerizes, binds to its cognate regulatory element called C120, and activates transcription.
Blue light causes TAEL to dimerize, bind C120, and activate transcription.
When illuminated with blue light, TAEL dimerizes, binds to its cognate regulatory element called C120, and activates transcription.
Blue light causes TAEL to dimerize, bind C120, and activate transcription.
When illuminated with blue light, TAEL dimerizes, binds to its cognate regulatory element called C120, and activates transcription.
Blue light causes TAEL to dimerize, bind C120, and activate transcription.
When illuminated with blue light, TAEL dimerizes, binds to its cognate regulatory element called C120, and activates transcription.
Blue light causes TAEL to dimerize, bind C120, and activate transcription.
When illuminated with blue light, TAEL dimerizes, binds to its cognate regulatory element called C120, and activates transcription.
Blue light causes TAEL to dimerize, bind C120, and activate transcription.
When illuminated with blue light, TAEL dimerizes, binds to its cognate regulatory element called C120, and activates transcription.
Blue-light illumination induces GFP expression detectable after 30 minutes and reaching more than 130-fold induction after 3 hours in transgenic zebrafish embryos using the TAEL/C120 system.
induction of GFP expression can first be detected after 30 min of illumination and reaches a peak of more than 130-fold induction after 3 h of light treatment
peak GFP induction 130 foldtime to first detection of GFP induction 30 min
Blue-light illumination induces GFP expression detectable after 30 minutes and reaching more than 130-fold induction after 3 hours in transgenic zebrafish embryos using the TAEL/C120 system.
induction of GFP expression can first be detected after 30 min of illumination and reaches a peak of more than 130-fold induction after 3 h of light treatment
peak GFP induction 130 foldtime to first detection of GFP induction 30 min
Blue-light illumination induces GFP expression detectable after 30 minutes and reaching more than 130-fold induction after 3 hours in transgenic zebrafish embryos using the TAEL/C120 system.
induction of GFP expression can first be detected after 30 min of illumination and reaches a peak of more than 130-fold induction after 3 h of light treatment
peak GFP induction 130 foldtime to first detection of GFP induction 30 min
Blue-light illumination induces GFP expression detectable after 30 minutes and reaching more than 130-fold induction after 3 hours in transgenic zebrafish embryos using the TAEL/C120 system.
induction of GFP expression can first be detected after 30 min of illumination and reaches a peak of more than 130-fold induction after 3 h of light treatment
peak GFP induction 130 foldtime to first detection of GFP induction 30 min
Blue-light illumination induces GFP expression detectable after 30 minutes and reaching more than 130-fold induction after 3 hours in transgenic zebrafish embryos using the TAEL/C120 system.
induction of GFP expression can first be detected after 30 min of illumination and reaches a peak of more than 130-fold induction after 3 h of light treatment
peak GFP induction 130 foldtime to first detection of GFP induction 30 min
The method is described as a versatile and easy-to-use approach for optogenetic gene expression.
This method is a versatile and easy-to-use approach for optogenetic gene expression.
The method is described as a versatile and easy-to-use approach for optogenetic gene expression.
This method is a versatile and easy-to-use approach for optogenetic gene expression.
The method is described as a versatile and easy-to-use approach for optogenetic gene expression.
This method is a versatile and easy-to-use approach for optogenetic gene expression.
The method is described as a versatile and easy-to-use approach for optogenetic gene expression.
This method is a versatile and easy-to-use approach for optogenetic gene expression.
The method is described as a versatile and easy-to-use approach for optogenetic gene expression.
This method is a versatile and easy-to-use approach for optogenetic gene expression.
Approval Evidence
5 sources4 linked approval claimsfirst-pass slugs qrt-pcr, quantitative-real-time-pcr, quantitative-real-time-pcr-qrt-pcr
These expression profiles were further validated by quantitative real-time PCR (qRT-PCR).
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We screened candidate NAC genes and validated their expression patterns using quantitative real-time PCR (qRT-PCR).
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From the quantitative analysis of gene expression by qRTPCR to the evaluation of mitochondrial function using induced pluripotent stem cells (iPSCs), the advances in diagnostic and research tools offer renewed hope.
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characterised their performance using GFP fluorescence assays and qRT-PCR
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Expression induction can be assessed by quantitative real-time PCR (qRT-PCR)
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candidate gene high expressionsupports
AkWRKY38 and AkWRKY53 exhibited high expression levels in Amorphophallus konjac under hormone treatments, Pcc infection, and abiotic stresses including low temperature, drought, and salt stress.
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stress responsive expressionsupports
Fourteen AkWRKY genes showed significantly differential expression under ABA, JA, SA, Pectobacterium carotovorum subsp. carotovorum infection, low temperature, drought, and salt stress.
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method capabilitysupports
Monitoring GFP transcript levels by qRT-PCR allowed quantification of transcriptional activation and deactivation kinetics and testing of multiple green/red and light/dark cycles on system performance.
Monitoring GFP transcript levels allowed us to quantify the kinetics of transcriptional activation and deactivation and to test the effect of both multiple green/red and light/dark cycles on system performance.
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research tool summarysupports
The review presents qRT-PCR and iPSC-based mitochondrial-function evaluation as advances in diagnostic and research tools for Alzheimer's disease.
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Comparisons
Source-backed strengths
The cited evidence supports qRT-PCR as a sensitive functional readout for transcript-level dynamics during repeated illumination cycling. It was specifically used to quantify kinetic responses and assess performance of light-responsive systems in Synechococcus sp. PCC 7002.
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Finally, we increased CcaS/CcaR system activity under green light through targeted genetic modifications to the <i>pCpcG2</i> output promoter.
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the CcaS/CcaR system originating from the cyanobacterium <i>Synechocystis</i> sp. PCC 6803 responded well to light wavelengths and intensities, with a 6-fold increased protein fluorescence output observed after 30 min of green light.
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The YF1/FixJ system of non-cyanobacterial origin showed poor performance with a maximum dynamic range of 1.5-fold despite several steps to improve this.
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induction of GFP expression can first be detected after 30 min of illumination and reaches a peak of more than 130-fold induction after 3 h of light treatment
qRT-PCR and automated 96-well microplate illumination and measurement address a similar problem space because they share transcription.
Shared frame: same top-level item type; shared target processes: transcription; same primary input modality: light
Compared with Iris
qRT-PCR and Iris address a similar problem space because they share transcription.
Shared frame: same top-level item type; shared target processes: transcription; same primary input modality: light
Relative tradeoffs: appears more independently replicated; looks easier to implement in practice.
Compared with open-source microplate reader
qRT-PCR and open-source microplate reader address a similar problem space because they share transcription.
Shared frame: same top-level item type; shared target processes: transcription; same primary input modality: light
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